expectancies, values, and achievement-related pursuits...

Expectancies, Values, and Achievement-Related Pursuits: The Case of Gender and STEM

Jacquelynne S. Eccles University of Michigan

Gender and STEM

BIEN, Berlin, July 3, 2014

Acknowledgements: This research was funded by grants from NIMH,

NSF, and NICHD to Eccles and by grants from NSF, Spencer Foundation and W.T. Grant to Eccles and Barber

I began my research work on gender and motivation with a quite specific question posed by the National Institute of Education in 1977:

WHY ARE FEMALES LESS LIKELY TO GO

INTO MATH AND PHYSICAL SCIENCE THAN MALES?

I became increasingly aware, however, that this question is a subset of a much more general question:

I became increasingly aware, however, that this question is a subset of a much more general question:

WHY DOES ANYONE DO ANYTHING?


My colleagues and I developed a theoretical framework to guide our research on both of these questions – a framework grounded in both psychological and

socio-cultural perspectives


My colleagues and I developed a theoretical framework to guide our research on both of these questions – a framework grounded in both psychological and

socio-cultural perspectives a framework that sought to incorporate both

personal agency and structure

Two Aspects of Choosing One’s Life Path

Personal Agency = Picking One’s Path Expectancy-value models of rational choice Identity development

Structural Forces = Opportunities and Barriers to Picking One’s Own Path Social forces that shape and restrict one’s

choices

Developing a Theory to Explain Gender and Achievement-Related

Choices My colleagues used these two perspectives to

develop a theoretical framework to guide a research program on the question posed by NIE.

Developing a Theory to Explain Gender and Achievement-Related

Choices My colleagues used these two perspectives to

develop a theoretical framework to guide a research program on the question posed by NIE.

WHY ARE FEMALES LESS LIKELY THAN MALES TO GO INTO THE PHYSICAL AND ENGINEERING SCIENCES?

Eccles et al. General Expectancy Value Model of Achievement Choices:

A. Cultural Milieu

1. Gender role stereotypes 2. Cultural stereotypes of subject matter and occupational characteristics 3. Family Demographics

E. Child's Perception of…

1. Socializer's beliefs, expectations, attitudes, and behaviors 2. Gender roles 3. Activity stereotypes and task demands

G. Child's Goals and General Self-Schemata

1. Personal and social identities 2. Possible and future selves 3. Self-concept of one's general/other abilities 4. Short-term goals 5. Long-term goals

I. Activity Specific Ability Self Concept and Expectations for Success

B. Socializer's Beliefs and Behaviors

C. Stable Child Characteristics 1. Aptitudes of child and sibs 2. Child gender 3. Birth order

D. Previous Achievement- Related Experiences

F. Child's Interpretations of Experience

H. Child's Affective Reactions and Memories

J. Subjective Task Value

1. Interest -enjoyment value 2. Utility Value 3. Attainment value 3.

4. Relative cost 5. Prior Investments

K. Achievement-Related Choices, Engagement and Persistence

Across Time

Presenter

Presentation Notes

A quick reminder of the Eccles Expectancy-Value model According to the Eccles’ Expectancy-Value Model, individuals’ educational and vocational choices are greatly influenced by their interests, values and expectations for success. More specifically, the model links achievement choices to interpretative systems like causal attributions, the input of socializers, gender role beliefs and cultural norms, to self-perceptions, aptitude, and to one’s perceptions of the task itself (Eccles, 1994). Applying the Eccles’ Expectancy-Value model, the current investigation, examines adolescents pursuit of information technology as a dynamic process that includes the consideration of the multiple social psychological and structural factors along adolescents developmental trajectories that were found to be influential on adolescents educational and occupational choices. For this talk, we will focus just on the far right hand boxes, marked in yellow.

Eccles et al. General Expectancy Value Model of Achievement Choices:

A. Cultural Milieu

1. Gender role stereotypes 2. Cultural stereotypes of subject matter and occupational characteristics 3. Family Demographics

E. Child's Perception of… 1.. Socializer's beliefs, expectations, attitudes, and behaviors

2. Gender roles 3. Activity stereotypes

and task demands

G. Child's Goals and General Self-Schemata

1. Personal and social identities 2. Possible and future selves 3. Self-concept of one's general/other abilities 4. Short-term goals 5. Long-term goals

I. Activity Specific Ability Self Concept and Expectations for Success

B. Socializer's Beliefs and Behaviors

C. Stable Child Characteristics 1. Aptitudes of child and sibs 2. Child gender 3. Birth order

D. Previous Achievement- Related Experiences

F. Child's Interpretations of Experience

H. Child's Affective Reactions and Memories

J. Subjective Task Value

1. Interest -enjoyment value 2. Utility Value 3. Attainment value 3.

4. Relative cost 5. Prior Investments

K. Achievement-Related Choices, Engagement and Persistence

Across Time

Presenter

Presentation Notes

A quick reminder of the Eccles Expectancy-Value model According to the Eccles’ Expectancy-Value Model, individuals’ educational and vocational choices are greatly influenced by their interests, values and expectations for success. More specifically, the model links achievement choices to interpretative systems like causal attributions, the input of socializers, gender role beliefs and cultural norms, to self-perceptions, aptitude, and to one’s perceptions of the task itself (Eccles, 1994). Applying the Eccles’ Expectancy-Value model, the current investigation, examines adolescents pursuit of information technology as a dynamic process that includes the consideration of the multiple social psychological and structural factors along adolescents developmental trajectories that were found to be influential on adolescents educational and occupational choices. For this talk, we will focus just on the far right hand boxes, marked in yellow.

Self and Identity

Today I am going to focus primarily on the most proximal psychological processes because these processes are directly linked to the self and to identity.

Self and Identity

Today I am going to focus primarily on the most proximal psychological processes because these processes are directly linked to the self and to identity.

Focus most on the components of subjective task value.

Subjective Task Value

Interests – Intrinsic enjoyment of doing the task or anticipated enjoyment of doing the task


Interests – Intrinsic enjoyment of doing the task or anticipated enjoyment of doing the task

Utility Value – The importance of the task for helping one accomplish one’s short or long term goals. Facilitate access to other opportunities or task Facilitate acquisition of other values resources Gain recognition from others


Attainment Value- Allow one to fulfill or enact critical aspects of one’s identity or central self-schema Demonstrate to oneself and others that one is the

kind of person that one would like to be (ideal self) Closely related to the stereotypes/schema one holds

about the association of various characteristics or activities with the tasks being considered

Subjective Task Value: Cost • Psychological Costs

• Fear of Success/Failure • Anticipated Anxiety

• Stereotype Threat • Link of Task Demands to Temperamental

“Traits” - leading to activation or anticipated activation of fear and anxiety



• Financial Costs • Lost Opportunities to Fulfill Other Goals or

to do Other Activities (Amy) • Implicit Beliefs (Me; Not Me) • Theories of Intelligence



• Financial Costs • Lost Opportunities to Fulfill Other Goals or to do Other Activities

• Social and Psychological Costs of Punishment or Rejection and of Violating Norms

Presenter

Presentation Notes

Now we go to structural component

Key Features of Model

1. Focuses on Choice not on Deficits

2. Points Out Importance of Studying the Origins of Individuals’ Perception of the Range of Possible Options

Key Features of Model 1. Focuses on the Fact that Choices are made

from a Wide Range of Positive Options

2. Focuses on the Hierarchical Nature of Both Expectancies and Subjective Task Values

3. These Hierarchies are Labile, Being Influenced by Immediate Social Context, and Developmental Tasks

How Does This Relate To Gender?

Personal Experiences

Subcultural Scripts, Beliefs, and Stereotypes

Societal Beliefs, Images, and Stereotypes

Personal Identities

Self Concepts

Personal Values

Personal Goals

Expectancies


Life Choices

Personal Experiences

Subcultural Scripts, Beliefs, and Stereotypes

Societal Beliefs, Images, and Stereotypes

Social Identities

Perception of Barriers And

Expected Behaviors Due to One’s Group

Membership

Other Aspects of Content

Salience

Expectancies


Life Choices

Gender and Both Ability Self Concepts and Subjective Task Value

Cultural Stereotypes about Which Gender is Supposed to be Good at Which Skills

Cultural Stereotypes about Which Gender is Supposed to be Interested or to Value Which Skills

Extensive Socialization Pressures to Make Sure These Stereotypes are Fulfilled

Gendered Achievement-Related Choices: STEM

My colleagues and I then used this framework to design a longitudinal study of gendered educational and occupational choices related to the mathematical, physical and engineering sciences.

I have time to give you only a couple of examples of this work.

Michigan Study of Adolescent Life Transitions (MSALT)

Waves 1-4 Jacque Eccles Carol Midgley Allan Wigfield

Jan Jacobs Connie Flanagan Harriet Feldlaufer

David Reuman Doug MacIver Dave Klingel

Doris Yee Christy Miller Buchanan

Waves 5-8 Jacque Eccles Bonnie Barber Lisa Colarossi

Deborah Jozefowicz Pam Frome Sarah Lord Mina Vida

Robert Roeser Laurie Meschke

OVERVIEW OF DESIGN AND SAMPLE: MICHIGAN STUDY OF ADOLESCENT LIFE

TRANSITIONS – MSALT

DESIGN: On-going Longitudinal Study of One Birth Cohort

Data Collected in Grades 6, 7, 10, 12; and again at Ages 20 and 25

Data Collected from Adolescents, Parents, and School – Most Using Survey Forms

SAMPLE: Nine School Districts Approximately 1,200 Adolescents Approximately 90% White Approximately 51% Female Working/Middle Class Background

Wave 1,2 3,4 5 6 7 8 9

Grade 6 7 10 12 12+2 12+6 12+9

Age 12 13 16 18 20 24 27

Year 83-'84 84-'85 88 90 92 96 99

MSALT DESIGN

MSALT Sample General Characteristics

School based sample drawn from 10 school districts in the small city communities surrounding Detroit.

Predominantly White, working and middle class families

Approximately 50% of sample of youth went on to some form of tertiary education

Two Basic Initial Questions

ARE THERE GENDER DIFFERENCES ON THESE SELF AND TASK BELIEFS? DO THE GENDER DIFFERENCES IN

THESE SELF-RELATED BELIEFS MEDIATE THE GENDER DIFFERENCES IN INVOVLEMENT?

Gender Differences in Ability Self Concepts – 7th Grade

3

3.5

4

4.5

5

5.5

6

Math English Sports

GirlsBoys

Gender Differences in Subjective Task Value – 7th Grade

3

3.5

4

4.5

5

5.5

6

6.5

Math English Sports

GirlsBoys

Conclusions

Gender Differences Occur across Several Domains for Both Ability Self Concepts and Subjective Task Values

Gender Differences Emerge Quite Young

But Do These Differences Mediate Gender Differences in Course Taking and Activity Involvement?

Predicting Number of Honors Math Classes (sex, DAT) N = 223 (honors students)

Gender

Math Aptitude

Number of Honors Math

Courses (R² = .08)

.15

.22

Predicting Number of Honors Math Classes N = 223 (honors students)

Gender

Math Aptitude

Self-Concept of Ability in

Math (R² = .06)

Interest in Math

(R² = .02)

Utility of Math

(R² = .04)

Number of Honors Math

Courses (R² = .19)

.15

.12

.14 .18

.14

.13

.25

Predicting Physical Science Class Enrollments

Number of Physical Science Courses

(R2 = .15)

Gender

Math Aptitude

.34

.16

Predicting # of Physical Science Classes (sex, DAT)

Number of Physical Science Courses

(R2 = .34)

Gender

Math Aptitude

Self Concept of PS Ability

Liking PS

Perceived Utility of PS

.16

.13

.09

.09

.20

.17 .09 .48

.19

Conclusion In this sample, the gender differences in utility value

were the strongest mediators of gender differences in math and physical science course enrollments.

A slightly different pattern is emerging for math in the CAB study: Math Ability Self Concept is having a stronger effect.

In this sample, the gender differences in all three expectancy – value beliefs mediated the gender differences in involvement in sports.

What about College Course Choices?

Wave 1,2 3,4 5 6 7 8 9

Grade 6 7 10 12 12+2 12+6 12+9

Age 12 13 16 18 20 24 27

Year 83-'84 84-'85 88 90 92 96 99

MSALT DESIGN

Specific Sample Characteristics for Analyses Reported Today

Those who participated at Wave 8 (age 25) Female N = 791 Male N = 575

Those who completed a college degree by Wave 8

Female N = 515 Male N = 377

Sex Differences in College Majors

0

20

40

60

80

100

120Fr

eque

ncy

Math/Science Biology Business Social Science

Female

Male

Sex Differences in Occupations

0

20

40

60

80

100

120

140

160

Fre

qu

ency

Math/Science Biology Business

Occupation at Age 25 by Sex

FemaleMale

Analyses 1: Between Sex

Logistic regression to test for mediators of sex differences in college Math/Engineering/Physical Science majors

Time 1 Measures: 12th Grade

Math/Physical Science Self-Concept of Ability

Math/PS Value and Usefulness Biology Self-Concept of Ability Biology Value and Usefulness English Self-Concept of Ability English Value and Usefulness High School Grade Point Average

Sex Differences in Domain Specific Self Concepts and Values

2

2.5

3

3.5

4

4.5

5

5.5M

ean

Valu

e

Math/Sci Value

Math/Sci Self C

oncept

Biology Self Concept

Biology Value

English Self Concept

English Value

Final GPA

Self Concept and Value at Age 18 by Sex

Female

Male

Time 1 Predictors of Physical Science and Engineering College Major

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Coefficient B

Presenter

Presentation Notes

Now what about college majors. We followed these youth into college and tested this same model for the association between gender and majoring in physical science, math or engineering in college. The bar represents the standardized b coefficient in a regression analysis. As you can see her gender explains a substantial amount of the variation in major selection.

Time 1 Predictors of Science College Major

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Coefficient B

Gender 1

Gender 2

Math Value

Math SC

Final GPA

Presenter

Presentation Notes

Here you can see that the magnitude of the gender effect is substantially reduced when high school GPA, and math ability self concepts and values are added to the equation.

Analyses: Within Sex Discriminant Function Analyses

Use age 20 General Ability SCs and

Occupational Values to predict College Major at age 25

Domain Specific Attractors: Self Concepts and Values

Non-Domain Attractors: General Achievement

Academic Choice

+

+

Domain Specific Attractors: Self Concepts and Values

Domain Specific

Detractors: Specific Costs

Non-Domain Detractors: Other Values and Self Concepts

Non-Domain Attractors: General Achievement

Academic Choice

+

-

-

+

Time 2 Measures: Age 20 Ability-Related

Math/Science General Ability Self Concept Efficacy for jobs requiring math/science

Intellectual Ability Self Concept Relative ability in logical and analytical thinking

High School Grade Point Average

Time 2 Measures: Occupational Values Job Flexibility

Does not require being away from family

Mental Challenge Opportunity to be creative and learn new things

Working with People Working with others

Autonomy Own Boss

Time 2 Measures: Comfort with Job Characteristics

Business Orientation: Comfort with tasks associated with being a supervisor

People Orientation: Comfort working with people and children

Sex Differences in Age 20 General Self Concepts and Values

2.5

3

3.5

4

4.5

5

5.5

6

Mea

n Va

lue

Math/Science Self Concept

Value Flexibility

Intellectual Self Concept

*Value Mental Challenge

Value Independent

Value Working with People

*Value Autonomy

Business Oriented

People Oriented

Final GPA

FemaleMale

Predicting Women’s M/E/PS and Biological Science College Major from

General Self-Concepts and Values at 20

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Discriminant Function Coefficient

Math/sci SelfConcept

People Oriented

Value workingwith people

Pridicting Biology vs. Other College Major -0.4 -0.2 0 0.2 0.4 0.6 0.8 1


Math/Sci SelfConcept

Intellectual SelfConcept

Final GPA

Working withpeople

Predicting Math /Science vs. Other College Major

Predicting Men’s M/E/PS and Biological Science College Major from General Self-

Concepts and Values at 20

-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5


Business Oriented

People Oriented

Final GPA

Value mental challenge

Value working with people

Math/Sci Self Concept

Value flexibility

Predicting Biology vs. Other College Major

-0.4 -0.2 0 0.2 0.4 0.6 0.8

Discriminant Function Coefficients

Math/Sci

Final GPA

Value Working withPeople

People oriented

Predicting Math/Science vs Other College Major

Predicting M/E/PS vs. Biology Major From General Self-Concepts and Values at

20

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8

Discriminant Function Coefficient for Females

Value working withPeople

Math/Sci self concept

People Oriented


Final Gpa

Business Oriented

-0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3

Discriminant Function Coefficient for Males

Value Work With People

People Oriented

Business Oriented

Value Flexibility

Final GPA

Math/Science Self -Concept

Intellectual Self Concept

Predicting M/E/PS vs. Social Science Major From General Self-Concepts and Values at 20

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Discriminant Function Coefficient for Females

Math/Sci Value


Final GPA

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Discriminant Function Coefficient for Males

Intellectual Self-Concept

Math/Sci Value

Final Gpa

Conclusions 1:

Strong support for the predictive power of constructs linked to the Expectancy Value Model. Domain Specific SCs and Values push both women and men

towards the related majors

Some evidence that more general values can also push people away from M/S/PS majors and towards Biology-Related majors

Sex differences in selection of M/E/PS college major

are largely accounted for by Expectancy Value Model

Conclusions 2

Even stronger support for both the push and pull aspects of the Eccles et al. Expectancy Value Model

Strong evidence that valuing having a job that allows one to work with and for people pushes individuals away from M/E/PS majors and pulls them toward the Biological Sciences

Applications

Interventions to increase the participation of females in M/E/PS need to focus on increasing women’s understanding that M/E/PS and Informational Technology jobs can help people and do involve working with people as well as increasing their confidence in their ability to succeed in these fields.

What have I Left Out?

Critical roles of parents and teachers We have this information on this in this sample and

another sample. Both are key in shaping gender differences in all

aspects of this model. On average, these processes reinforce traditional

gender role self images and choices.

What have I Left Out? The other psychological and social processes that

drive women and men out of non-traditional fields

I am particularly interested in the processes that influence interest in and intense passion for particular activities. The role that ongoing emotional

experiences play in shaping more stable and enduring interests, “passions”, and thus the differential Subjective Task Value of various activities.

Thank You

More details and copies can be found at www.rcgd.isr.umich.edu/garp/

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